Microsatellite DNA Analysis of Genetic Diversity and Parentage Testing in Popular Dog Breeds in India
Bibliographic record
Abstract
For the parentage testing in canine microsatellite length polymorphism markers were used to check the efficacy of the markers. In the current study 5’ fluorescently labeled 12 SSR markers were used to check the use of the markers in popular owned-dog breeds (Labrador, German Shepherd, Pug, Mudhol Hound, Tibetan Mastiff, Gaddi dog, Beagle, Belgian Malinois, Pointer, and Cane Corso) maintained of India (not necessarily indigenous breeds). The number of alleles, heterozygosity, polymorphism information content, and probability of exclusion were determined for all the markers to check the effectiveness of the markers. The mean number of alleles per locus ranged from 5 to 29 and the effective number of alleles ranged from 3.6 to 15.2. The expected heterozygosity was greater than 0.73. The population inbreeding coefficient (FIS) demonstrated that there was no inbreeding in the breeds studied, as the samples were collected from owners and dog breeders belonging to various states, including Punjab, Haryana, Himachal Pradesh, and Karnataka. The polymorphism information content and the probability of the exclusion values were greater than 0.65. the combined probability of exclusion for all the breeds was (2.82E-12) 0.99999995. The results indicated that the selected 12 markers are effective enough to determine the parentage of the dogs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".